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GO: a cluster algorithm for graph visualization
journal contribution
posted on 2023-05-18, 06:34 authored by Huang, X, Huang, WAs we are in the big data age, graph data such as user networks in Facebook and Flickr becomes large. How to reduce the visual complexity of a graph layout is a challenging problem. Clustering graphs is regarded as one of effective ways to address this problem. Most of current graph visualization systems, however, directly use existing clustering algorithms that are not originally developed for the visualization purpose. For graph visualization, a clustering algorithm should meet specific requirements such as the sufficient size of clusters, and automatic determination of the number of clusters. After identifying the requirements of clustering graphs for visualization, in this paper we present a new clustering algorithm that is particularly designed for visualization so as to reduce the visual complexity of a layout, together with a strategy for improving the scalability of our algorithm. Experiments have demonstrated that our proposed algorithm is capable of detecting clusters in a way that is required in graph visualization.
History
Publication title
Journal of Visual Languages and ComputingVolume
28Pagination
71-82ISSN
1045-926XPublisher
Academic Press Ltd Elsevier Science LtdPlace of publication
24-28 Oval Rd, London, England, Nw1 7DxRights statement
Copyright 2014 Elsevier Ltd.Repository Status
- Restricted